Research Areas

Faculty and students in the University of Idaho Computer Science Department are actively engaged in several significant research areas. In addition to conducting research, we consider it our responsibility to disseminate the results of our work through high quality scientific publications. As an integral part of our graduate student mentoring we strive to engage our students our research and in the publication process.

Information Assurance & Computer Security

Computer Science faculty and students at the University of Idaho have been actively engage in researching theory, tools and techniques to enhance security of computer systems, information transmission, and information protection. To find out more about current activities visit the Center for Secure and Dependable System (CSDS) web site.

Our faculty and students have also designed and implemented a hands-on laboratory where students can investigate threats to and protection of computer system.

Collaborative Virtual Education

Clint Jeffery wants to make Computer Science a little easier and more fun by virtue of a serious game called CVE (Collaborative Virtual Education). The "game" features social interactions in 3D with instructors and fellow students, along with collaborative IDE tools which will make it easier to get live on-line help. So far, the project has built a simple model of Janssen Engineering Building, where the Computer Science Department is located. The current CVE program development is an NSF-funded open source software project. To find out more, visit the CVE website.

Evolutionary Computation

The evolutionary computation group studies the process of evolving better solutions from a population of potentially good solutions. This is a process similar to a farmer breeding a better cow from a herd of cows. These techniques are useful for complex problems for which no known efficient (polynomial) algorithms exist or where the search space is immense.

Specifically this group has looked at several techniques of breeding protein classifiers for biological problems and training teams of robots to cooperate. The group also works on theory to understand how subtle interactions in a problem representation called epistasis that makes the problems more difficult for these general optimizers.

Bioinformatics

Faculty and students have studied novel algorithms for phylogenetics and protein classification. Student work has included cancer simulations to study the development of breast cancer at the genetic and cellular levels.